TensorCamera shows a black screen

[cod3kid]

This code is a slightly modified version of https://github.com/tensorflow/tfjs-examples/blob/master/react-native/pose-detection/App.tsx

I have replaced Camera with CameraView as Camera is no longer a React Component.
When autoRender is true, it shows a black screen but plots the pose detection points
When autoRender is false, updatePreview() causes an error

import React, {useEffect, useState, useRef} from 'react';
import {StyleSheet, Text, View, Dimensions, Platform} from 'react-native';

import {Camera, CameraView} from 'expo-camera';

import * as tf from '@tensorflow/tfjs';
import * as posedetection from '@tensorflow-models/pose-detection';
import * as ScreenOrientation from 'expo-screen-orientation';
import {
  bundleResourceIO,
  cameraWithTensors,
} from '@tensorflow/tfjs-react-native';
import Svg, {Circle} from 'react-native-svg';
import '@tensorflow/tfjs-backend-webgpu';
import '@tensorflow/tfjs-backend-webgl';

// tslint:disable-next-line: variable-name
const TensorCamera = cameraWithTensors(CameraView);

const IS_ANDROID = Platform.OS === 'android';
const IS_IOS = Platform.OS === 'ios';

// Camera preview size.
//
// From experiments, to render camera feed without distortion, 16:9 ratio
// should be used fo iOS devices and 4:3 ratio should be used for android
// devices.
//
// This might not cover all cases.
const CAM_PREVIEW_WIDTH = Dimensions.get('window').width;
const CAM_PREVIEW_HEIGHT = CAM_PREVIEW_WIDTH / (IS_IOS ? 9 / 16 : 3 / 4);

// The score threshold for pose detection results.
const MIN_KEYPOINT_SCORE = 0.3;

// The size of the resized output from TensorCamera.
//
// For movenet, the size here doesn't matter too much because the model will
// preprocess the input (crop, resize, etc). For best result, use the size that
// doesn't distort the image.
const OUTPUT_TENSOR_WIDTH = 180;
const OUTPUT_TENSOR_HEIGHT = OUTPUT_TENSOR_WIDTH / (IS_IOS ? 9 / 16 : 3 / 4);

// Whether to auto-render TensorCamera preview.
const AUTO_RENDER = false;

// Whether to load model from app bundle (true) or through network (false).
const LOAD_MODEL_FROM_BUNDLE = false;

export default function App() {
  const cameraRef = useRef(null);
  const [tfReady, setTfReady] = useState(false);
  const [model, setModel] = useState(null);
  const [poses, setPoses] = useState(null);
  const [fps, setFps] = useState(0);
  const [orientation, setOrientation] = useState(null);
  const [cameraType, setCameraType] = useState('front');
  // Use `useRef` so that changing it won't trigger a re-render.
  //
  // - null: unset (initial value).
  // - 0: animation frame/loop has been canceled.
  // - >0: animation frame has been scheduled.
  const rafId = useRef(null);

  useEffect(() => {
    async function prepare() {
      rafId.current = null;

      // Set initial orientation.
      const curOrientation = await ScreenOrientation.getOrientationAsync();
      setOrientation(curOrientation);

      // Listens to orientation change.
      ScreenOrientation.addOrientationChangeListener(event => {
        setOrientation(event.orientationInfo.orientation);
      });

      // Camera permission.
      await Camera.requestCameraPermissionsAsync();

      // Wait for tfjs to initialize the backend.
      await tf.ready();

      // Load movenet model.
      // https://github.com/tensorflow/tfjs-models/tree/master/pose-detection
      const movenetModelConfig = {
        modelType: posedetection.movenet.modelType.SINGLEPOSE_LIGHTNING,
        enableSmoothing: true,
        runtime: 'tfjs',
      };
      // if (LOAD_MODEL_FROM_BUNDLE) {
      //   const modelJson = require('./offline_model/model.json');
      //   const modelWeights1 = require('./offline_model/group1-shard1of2.bin');
      //   const modelWeights2 = require('./offline_model/group1-shard2of2.bin');
      //   movenetModelConfig.modelUrl = bundleResourceIO(modelJson, [
      //     modelWeights1,
      //     modelWeights2,
      //   ]);
      // }
      const modelTemp = await posedetection.createDetector(
        posedetection.SupportedModels.MoveNet,
        movenetModelConfig,
      );
      setModel(modelTemp);

      // Ready!
      setTfReady(true);
    }

    prepare();
  }, []);

  useEffect(() => {
    // Called when the app is unmounted.
    return () => {
      if (rafId.current != null && rafId.current !== 0) {
        cancelAnimationFrame(rafId.current);
        rafId.current = 0;
      }
    };
  }, []);

  const handleCameraStream = async (images, updatePreview = () => {}, gl) => {
    const loop = async () => {
      // Get the tensor and run pose detection.
      console.log('n');
      try {
        const imageTensor = images.next().value;

        const startTs = Date.now();
        const poses = await model.estimatePoses(
          imageTensor,
          undefined,
          Date.now(),
        );
        const latency = Date.now() - startTs;
        setFps(Math.floor(1000 / latency));
        setPoses(poses);
        tf.dispose([imageTensor]);

        if (rafId.current === 0) {
          return;
        }
        // Render camera preview manually when autorender=false.
        if (!AUTO_RENDER) {
          // console.log('before', updatePreview());
          updatePreview();
          console.log('after');
          gl.endFrameEXP();
        }

        rafId.current = requestAnimationFrame(loop);
      } catch (ex) {
        console.log('error', ex);
      }
    };

    loop();
  };

  const renderPose = () => {
    if (poses != null && poses.length > 0) {
      const keypoints = poses[0].keypoints
        .filter(k => (k.score ?? 0) > MIN_KEYPOINT_SCORE)
        .map(k => {
          // Flip horizontally on android or when using back camera on iOS.
          const flipX = IS_ANDROID || cameraType === 'back';
          const x = flipX ? getOutputTensorWidth() - k.x : k.x;
          const y = k.y;
          const cx =
            (x / getOutputTensorWidth()) *
            (isPortrait() ? CAM_PREVIEW_WIDTH : CAM_PREVIEW_HEIGHT);
          const cy =
            (y / getOutputTensorHeight()) *
            (isPortrait() ? CAM_PREVIEW_HEIGHT : CAM_PREVIEW_WIDTH);
          return (
            <Circle
              key={`skeletonkp_${k.name}`}
              cx={cx}
              cy={cy}
              r="4"
              strokeWidth="2"
              fill="#00AA00"
              stroke="white"
            />
          );
        });

      return <Svg style={styles.svg}>{keypoints}</Svg>;
    } else {
      return <View></View>;
    }
  };

  const renderFps = () => {
    return (
      <View style={styles.fpsContainer}>
        <Text>FPS: {fps}</Text>
      </View>
    );
  };

  const renderCameraTypeSwitcher = () => {
    return (
      <View
        style={styles.cameraTypeSwitcher}
        onTouchEnd={handleSwitchCameraType}>
        <Text>
          Switch to {cameraType === 'front' ? 'back' : 'front'} camera
        </Text>
      </View>
    );
  };

  const handleSwitchCameraType = () => {
    if (cameraType === 'front') {
      setCameraType('back');
    } else {
      setCameraType('front');
    }
  };

  const isPortrait = () => {
    return (
      orientation === ScreenOrientation.Orientation.PORTRAIT_UP ||
      orientation === ScreenOrientation.Orientation.PORTRAIT_DOWN
    );
  };

  const getOutputTensorWidth = () => {
    // On iOS landscape mode, switch width and height of the output tensor to
    // get better result. Without this, the image stored in the output tensor
    // would be stretched too much.
    //
    // Same for getOutputTensorHeight below.
    return isPortrait() || IS_ANDROID
      ? OUTPUT_TENSOR_WIDTH
      : OUTPUT_TENSOR_HEIGHT;
  };

  const getOutputTensorHeight = () => {
    return isPortrait() || IS_ANDROID
      ? OUTPUT_TENSOR_HEIGHT
      : OUTPUT_TENSOR_WIDTH;
  };

  const getTextureRotationAngleInDegrees = () => {
    // On Android, the camera texture will rotate behind the scene as the phone
    // changes orientation, so we don't need to rotate it in TensorCamera.
    if (IS_ANDROID) {
      return 0;
    }

    // For iOS, the camera texture won't rotate automatically. Calculate the
    // rotation angles here which will be passed to TensorCamera to rotate it
    // internally.
    switch (orientation) {
      // Not supported on iOS as of 11/2021, but add it here just in case.
      case ScreenOrientation.Orientation.PORTRAIT_DOWN:
        return 180;
      case ScreenOrientation.Orientation.LANDSCAPE_LEFT:
        return cameraType === 'front' ? 270 : 90;
      case ScreenOrientation.Orientation.LANDSCAPE_RIGHT:
        return cameraType === 'back' ? 90 : 270;
      default:
        return 0;
    }
  };

  if (!tfReady) {
    return (
      <View style={styles.loadingMsg}>
        <Text>Loading...</Text>
      </View>
    );
  } else {
    return (
      // Note that you don't need to specify `cameraTextureWidth` and
      // `cameraTextureHeight` prop in `TensorCamera` below.
      <View
        style={
          isPortrait() ? styles.containerPortrait : styles.containerLandscape
        }>
        <TensorCamera
          // ref={cameraRef}
          style={styles.camera}
          autorender={AUTO_RENDER}
          type={cameraType}
          // tensor related props
          resizeWidth={getOutputTensorWidth()}
          resizeHeight={getOutputTensorHeight()}
          resizeDepth={3}
          rotation={getTextureRotationAngleInDegrees()}
          onReady={handleCameraStream}
        />
        {/* {renderPose()} */}
        {renderFps()}
        {renderCameraTypeSwitcher()}
      </View>
    );
  }
}

const styles = StyleSheet.create({
  containerPortrait: {
    position: 'relative',
    width: CAM_PREVIEW_WIDTH,
    height: CAM_PREVIEW_HEIGHT,
    marginTop: Dimensions.get('window').height / 2 - CAM_PREVIEW_HEIGHT / 2,
  },
  containerLandscape: {
    position: 'relative',
    width: CAM_PREVIEW_HEIGHT,
    height: CAM_PREVIEW_WIDTH,
    marginLeft: Dimensions.get('window').height / 2 - CAM_PREVIEW_HEIGHT / 2,
  },
  loadingMsg: {
    position: 'absolute',
    width: '100%',
    height: '100%',
    alignItems: 'center',
    justifyContent: 'center',
  },
  camera: {
    width: '100%',
    height: '100%',
    zIndex: 1,
  },
  svg: {
    width: '100%',
    height: '100%',
    position: 'absolute',
    zIndex: 30,
  },
  fpsContainer: {
    position: 'absolute',
    top: 10,
    left: 10,
    width: 80,
    alignItems: 'center',
    backgroundColor: 'rgba(255, 255, 255, .7)',
    borderRadius: 2,
    padding: 8,
    zIndex: 20,
  },
  cameraTypeSwitcher: {
    position: 'absolute',
    top: 10,
    right: 10,
    width: 180,
    alignItems: 'center',
    backgroundColor: 'rgba(255, 255, 255, .7)',
    borderRadius: 2,
    padding: 8,
    zIndex: 20,
  },
});

[shmishra99]

Hi @cod3kid ,

I am not able to replicate this issue. Coluld you please give a try as per the instruction given in the following comment and let me know if it is resolving your issue. comment

Thank You!!

[cod3kid]

@shmishra99 Adding tf.env().set('WEBGL_PACK_DEPTHWISECONV', false); doesn't fix my issue

[GrandChieftain]

Suffering from the same problem right now, just got my tflite model to load just for a black screen, great

Edit: this may sound dumb but this was my problem, make sure you request for camera permissions first